In their work, [1]} have studied and categorized a number of stereo algorithms for dense disparity or depth estimation based on their processing steps. From their observations they have derived a general processing pipeline which provides a basic blueprint for most modern stereo algorithms, as well as for our approach proposed in this work, as illustrated in fig:stereopipelineoverview. In this, the estimation of dense disparity maps can be subdivided into three subsequent steps, which are made of smaller building blocks. In the following, we will look at each individual processing step, give a short overview of its task, and subsequently provide a detailed description on how we have instantiated it in our proposed approach.
